code: def load_df(path, cuda=False):
      """Load dataframe for model and func benchmarks assumining directory is structured as
        path
          |_func_benchmarks.csv
          |_model_benchmarks.csv
          |_func_benchmarks_cuda.csv (optional)
          |_model_benchmarks_cuda.csv (optional)
      Args:
          path (str): path containing model and func benchmarks
          cuda (bool) : if set to true, read the corresponding func and model benchmarks for cuda
      Returns: tuple of pd.DataFrames containing func and model benchmarks with dates
      """
      postfix = "_cuda" if cuda else ""
      func_path = os.path.join(path, f"func_benchmarks{postfix}.csv")
      model_path = os.path.join(path, f"model_benchmarks{postfix}.csv")
  
      func_df, model_df = pd.DataFrame(), pd.DataFrame()
      if os.path.exists(func_path):
          func_df = pd.read_csv(func_path)
      if os.path.exists(model_path):
          model_df = pd.read_csv(model_path)
  
      return func_df, model_df
  
file_path: CrypTen/benchmarks/dash_app/load_data.py
imports: import os
  import pandas
label_desc: Use image node_id 2 for calling a global function with example usage: load_df(path, cuda) and returns: func_df,  model_df